After performing two rounds of self and cross-attention, we aggregate all the transformed local features into a single scalar score predicting the match between \(A\)  and \(B\) . The aggregation is inspired by the Graph Matching Networks [1]}:
\(s = h \left( \sum _{i} \ \alpha _i \odot \ f (\mathbf {z}_i) \right),\quad (\alpha _i)_k = \frac{\exp g_k(\mathbf {z}_i)}{\sum _j \exp g_k(\mathbf {z}_j)}\,,\) 
